SIENTIAPDE-1646

SIENTIAPDE-1646 Refactor MLFlow tests and update artifact handling

- Enhanced test cases for MLFlow to improve clarity and accuracy in data handling.
- Updated references in tests to use 'evaluation_data.csv' and 'test_data.csv' instead of 'retrain_input.csv' and 'train_data.csv'.
- Introduced a new helper function for creating prediction frames to streamline test setup.

laborious/activities/mlflow.py

@@ -559,7 +559,7 @@ class MLFlow(SientiaMonitoring):
                     evaluation_csv = Path(tmp_dir) / 'evaluation_data.csv'
                     data.to_csv(raw_csv, index=False)
                     evaluation_data.to_csv(evaluation_csv, index=False)
-                    
+
                     mlflow.log_artifact(str(raw_csv))
                     mlflow.log_artifact(str(evaluation_csv))
                 finally:

laborious/worker/worker.py

@@ -216,7 +216,7 @@ async def main():
                 activities.export_data_to_postgres,
             ],
             logger=logger,
-            runtime='core'
+            runtime='core',
         ),
         prepare_worker(
             temporal_client=temporal_client,
@@ -229,7 +229,7 @@ async def main():
                 activities.export_data_to_postgres,
             ],
             logger=logger,
-            runtime='core'
+            runtime='core',
         ),
         prepare_worker(
             temporal_client=temporal_client,